Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.
Katarzyna NabrdalikKrzysztof IrlikYanda MengHanna KwiendaczJulia PiaśnikMirela HendelPaweł IgnacyJustyna KulpaKamil KeglerMikołaj HerbaSylwia BoczekEffendy Bin HashimZhuangzhi GaoJanusz GumprechtYalin ZhengGregory Y H LipUazman AlamPublished in: Cardiovascular diabetology (2024)
This is a part of the Silesia Diabetes-Heart Project (Clinical-Trials.gov Identifier: NCT05626413).
Keyphrases
- artificial intelligence
- deep learning
- machine learning
- type diabetes
- clinical trial
- big data
- cardiovascular disease
- optical coherence tomography
- diabetic retinopathy
- glycemic control
- heart failure
- convolutional neural network
- atrial fibrillation
- heart rate variability
- quality improvement
- left ventricular
- heart rate
- blood pressure
- open label
- optic nerve
- weight loss
- double blind